CN111884694B - Beam forming control method and device, electronic equipment and storage medium - Google Patents
Beam forming control method and device, electronic equipment and storage medium Download PDFInfo
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- CN111884694B CN111884694B CN202010736417.XA CN202010736417A CN111884694B CN 111884694 B CN111884694 B CN 111884694B CN 202010736417 A CN202010736417 A CN 202010736417A CN 111884694 B CN111884694 B CN 111884694B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/0842—Weighted combining
- H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
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Abstract
The embodiment of the application provides a beam forming control method, a beam forming control device, electronic equipment and a storage medium, wherein time information of target equipment reaching a target area is obtained, a target weight vector is determined according to the time information, beam forming is carried out according to the target weight vector, so that signal coverage is carried out on the target area, and the time of the target equipment reaching the target area can be accurately corresponding according to the determination of the target weight vector according to the time information.
Description
Technical Field
The present application relates to the field of 5G technologies, and in particular, to a method and an apparatus for controlling beamforming, an electronic device, and a storage medium.
Background
This section is intended to provide a background or context to the embodiments of the application that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
With the official business of the fifth generation mobile communication technology (5 th generation mobile networks, 5G), the 5G era of everything interconnection is coming. Since the high frequency band of 5G has high path loss and poor diffraction capability, it is necessary to combine with large-scale antenna array and beamforming technologies to achieve high gain to resist high path loss and signal attenuation.
In recent years, high-speed rails are rapidly developed, the high-speed rails serve as an important public praise scene, and the brand public praise of operators is directly influenced by the 5G user experience. In a high-speed rail scene, a private network coverage scheme is adopted at present, namely, an independent station is used for covering a high-speed rail train along a high-speed rail, and when the train passes through, the signal coverage of the train is realized by utilizing self-adaptive beam forming.
However, with the increase of the speed of the train and the connection amount of the terminal devices on the train, by detecting the signal condition when the train passes through and performing the adaptive beamforming scheme, the problem of poor real-time performance and accuracy of beamforming control exists, and the quality of the signal received by the terminal devices is affected.
Disclosure of Invention
The application provides a beamforming control method, a beamforming control device, electronic equipment and a storage medium, which are used for solving the problems that the real-time performance and accuracy of beamforming control are poor and the quality of a signal received by terminal equipment is influenced.
According to a first aspect of an embodiment of the present application, there is provided a beamforming control method, including:
acquiring time information of target equipment reaching a target area; determining a target weight vector according to the time information; and carrying out beam forming according to the target weight vector so as to carry out signal coverage on the target area.
In one possible implementation, the target area includes a target cell; acquiring time information of a target device reaching a target area, comprising:
acquiring user connection information in a target cell; and determining the time information of the target equipment reaching the target cell according to the time domain characteristics of the user connection information.
In a possible implementation manner, the determining, by the time domain feature of the user connection information, time information of the target device reaching the target cell includes: acquiring time domain periodic pulses of user connection information; and determining the time information of the target equipment reaching the target cell according to the distribution of the time domain periodic pulse.
In a possible implementation manner, after obtaining time information of the target device reaching the target area, the method further includes: acquiring a preset base station connection model; the base station connection model is used for representing a base station connection rule in the target area; and migrating the resident signal connected with the base station in the target area to the base station in the non-target area according to the base station connection model, wherein the resident signal is a connection signal of resident equipment connected with the base station in the target area.
In a possible implementation manner, migrating a resident signal connected to a base station in the target area to a base station in a non-target area according to the base station connection model includes: determining a target time window according to the base station connection model, wherein the target time window is used for representing the time of the target equipment reaching a target area; and migrating the resident signal connected with the base station in the target area to the base station in the non-target area in the target time window.
In a possible implementation manner, the time information includes a target time window, where the target time window is used to characterize the time when the target device reaches a target area, and determining a target weight vector according to the time information includes: acquiring signal intensity information in the target time window; and determining a target weight vector according to the signal intensity information.
In one possible implementation, the signal strength information is used to characterize the signal strength of each weight vector; wherein each weight vector corresponds to a plurality of signal strength values; determining a target weight vector according to the signal strength information, comprising: acquiring signal strength values respectively corresponding to the weight vectors; and determining a target weight vector according to the mean value of the signal strength values corresponding to the weight vectors and the good proportion value of the signal strength values corresponding to the weight vectors, wherein the good proportion value is used for representing the proportion of a plurality of signal strength values corresponding to the weight vectors, which is greater than a preset signal strength threshold value.
In a possible implementation manner, determining a target weight vector according to a mean value of the signal strength values corresponding to the weight vectors and a good ratio of the signal strength values corresponding to the weight vectors includes: if the unique weight vector exists in each weight vector, the condition that the good occupation ratio of the corresponding signal intensity value is the maximum and the mean value of the corresponding signal intensity value is greater than a preset signal coverage threshold value is met, determining the unique weight vector as a target weight vector; if at least two weight vectors exist in each weight vector, the condition that the good occupation ratio of the corresponding signal intensity value is the largest is met, and the mean value of the corresponding signal intensity value is larger than a preset signal coverage threshold value, the mean value of the signal intensity values in the at least two weight vectors is larger, and the weight vector is determined as a target weight vector.
In a possible implementation manner, after determining the target weight vector according to the time information, the method further includes: acquiring signals of the target area according to preset acquisition configuration information to obtain a check signal; and calibrating the target weight vector according to the relation between the signal intensity of the target weight vector and the signal intensity of the check signal.
According to a second aspect of the embodiments of the present application, there is provided a beamforming control apparatus, including:
the acquisition module is used for acquiring the time information of the target equipment reaching the target area; the determining module is used for determining a target weight vector according to the time information; and the forming module is used for carrying out beam forming according to the target weight vector so as to carry out signal coverage on the target area.
In one possible implementation, the target area includes a target cell; the obtaining module is specifically configured to: acquiring user connection information in a target cell; and determining the time information of the target equipment reaching the target cell according to the time domain characteristics of the user connection information.
In a possible implementation manner, the time domain feature includes a time domain periodic pulse, and when determining, according to the time domain feature of the user connection information, time information that the target device reaches the target cell, the obtaining module is specifically configured to: acquiring time domain periodic pulses of user connection information; and determining the time information of the target equipment reaching the target cell according to the distribution of the time domain periodic pulse.
In a possible implementation manner, the beamforming control apparatus further includes: the migration module is used for acquiring a preset base station connection model after acquiring time information of the target equipment reaching the target area; the base station connection model is used for representing a base station connection rule in the target area; and migrating the resident signal connected with the base station in the target area to the base station in the non-target area according to the base station connection model, wherein the resident signal is a connection signal of resident equipment connected with the base station in the target area.
In a possible implementation manner, when migrating the resident signal connected to the base station in the target area to the base station in the non-target area according to the base station connection model, the migration module is specifically configured to: determining a target time window according to the base station connection model, wherein the target time window is used for representing the time of the target equipment reaching a target area; and migrating the resident signal connected with the base station in the target area to the base station in the non-target area in the target time window.
In a possible implementation manner, the time information includes a target time window, the target time window is used to characterize a time when the target device reaches a target area, and the determining module is specifically configured to: acquiring signal intensity information in the target time window; and determining a target weight vector according to the signal intensity information.
In one possible implementation, the signal strength information is used to characterize the signal strength of each weight vector; wherein each weight vector corresponds to a plurality of signal strength values; the determining module is specifically configured to, when determining the target weight vector according to the signal strength information: acquiring signal strength values respectively corresponding to the weight vectors; and determining a target weight vector according to the mean value of the signal strength values corresponding to the weight vectors and the good proportion value of the signal strength values corresponding to the weight vectors, wherein the good proportion value is used for representing the proportion of a plurality of signal strength values corresponding to the weight vectors, which is greater than a preset signal strength threshold value.
In a possible implementation manner, when the determining module determines the target weight vector according to the mean value of the signal strength values corresponding to the weight vectors and the good ratio of the signal strength values corresponding to the weight vectors, the determining module is specifically configured to: if the unique weight vector exists in each weight vector, the condition that the good occupation ratio of the corresponding signal intensity value is the maximum and the mean value of the corresponding signal intensity value is greater than a preset signal coverage threshold value is met, determining the unique weight vector as a target weight vector; if at least two weight vectors exist in each weight vector, the condition that the good occupation ratio of the corresponding signal intensity value is the largest is met, and the mean value of the corresponding signal intensity value is larger than a preset signal coverage threshold value, the mean value of the signal intensity values in the at least two weight vectors is larger, and the weight vector is determined as a target weight vector.
In a possible implementation manner, the beamforming control apparatus further includes: the calibration module is used for acquiring signals of the target area according to preset acquisition configuration information after determining a target weight vector according to the time information to obtain a check signal; and calibrating the target weight vector according to the relation between the signal intensity of the target weight vector and the signal intensity of the check signal.
According to a third aspect of embodiments of the present application, there is provided an electronic device, comprising: a memory, a processor, and a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to perform the beamforming control method according to any of the first aspect of the embodiments of the present application.
According to a fourth aspect of embodiments of the present application, there is provided a computer-readable storage medium having stored therein computer-executable instructions, which when executed by a processor, are configured to implement the beamforming control method according to any one of the first aspect of embodiments of the present application.
According to the beam forming control method, the beam forming control device, the electronic equipment and the storage medium, the time information of the target equipment reaching the target area is obtained, the target weight vector is determined according to the time information, beam forming is carried out according to the target weight vector, and signal coverage is carried out on the target area.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is an application scenario diagram of a beamforming control method provided in an embodiment of the present application;
fig. 2 is a flowchart of a beamforming control method according to an embodiment of the present application;
fig. 3 is a schematic diagram of beamforming provided in an embodiment of the present application;
fig. 4 is a flowchart of a beamforming control method according to another embodiment of the present application;
fig. 5 is a schematic diagram of a time domain feature of user connection information according to an embodiment of the present disclosure;
FIG. 6 is a flowchart of step S202 in the embodiment shown in FIG. 4;
FIG. 7 is a schematic diagram of a time-domain periodic pulse according to an embodiment of the present application;
FIG. 8 is a flowchart of step S204 in the embodiment shown in FIG. 4;
FIG. 9 is a schematic diagram of a target time window provided in an embodiment of the present application;
FIG. 10 is a flowchart of step S206 in the embodiment shown in FIG. 4;
FIG. 11 is a schematic diagram of determining a target weight vector according to an embodiment of the present application;
FIG. 12 is a schematic diagram of another embodiment of the present application for determining target weight vectors;
fig. 13 is a comparison graph of good ratio of signal strength generated by the beamforming method provided in the embodiment of the present application and the signal strength generated by the conventional beamforming method;
fig. 14 is a flowchart of a beamforming control method according to another embodiment of the present application;
fig. 15 is a schematic structural diagram of a beamforming control apparatus according to an embodiment of the present application;
fig. 16 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Specific embodiments of the present application have been shown by way of example in the drawings and will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The following explains an application scenario of the embodiment of the present application:
fig. 1 is an application scenario diagram of a beamforming control method provided in the embodiment of the present application, and as shown in fig. 1, an execution subject of the beamforming control method provided in the embodiment of the present application may be a 5G base station, and more specifically, the 5G base station is applied to a high-speed rail-oriented 5G signal private network coverage scheme. The 5G base station is arranged along the high-speed rail, and realizes signal coverage of the high-speed rail train by transmitting beams in a coverage range.
In the prior art, a private network coverage scheme adopted by a high-speed rail is to cover the high-speed rail with an independent station along the high-speed rail, and areas outside the high-speed rail are mainly covered by other public network stations, but common users around the high-speed rail cannot avoid occupying a high-speed rail cell because the private network and the public network wireless signals are inevitably staggered and overlapped. Before the high-speed train arrives, the high-speed railway cell carries out beam forming based on the position and the coverage requirement of a common user, and when the high-speed train arrives each time, the 5G base station readjusts the beam forming according to the requirement of the high-speed railway user so as to meet the signal coverage of the high-speed railway user.
However, in a high-speed rail scene, the moving speed of the train is high, and the number of high-speed rail users is large, but the conventional adaptive beamforming method needs to obtain the current load condition in the high-speed rail cell to perform adaptive beamforming control, so that the problems of poor real-time performance and low control accuracy of beamforming control exist, and the signal quality of the high-speed rail users is affected.
The following describes the technical solution of the present application and how to solve the above technical problems in detail by specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Fig. 2 is a flowchart of a beamforming control method provided in an embodiment of the present application, which is applied to a 5G base station or an electronic device in the 5G base station, as shown in fig. 2, the beamforming control method provided in this embodiment includes the following steps:
step S101, acquiring time information of the target device reaching the target area.
Illustratively, the target device may be a terminal device having a communication function, such as a mobile phone, a tablet computer with a network function, and the like. More specifically, in a high-speed rail signal coverage scenario, the target device refers to a terminal device used by a user in a high-speed rail train. Along with the high-speed rapid movement, the target equipment in the high-speed train moves at a high speed, and can be connected with the 5G base station to receive the 5G signal in the high-speed moving process.
The time information refers to information related to time when the target device arrives at the target area, and the time information may be a time point or a time period, which is not specifically limited herein. Since the user of the target device carries a vehicle such as a high-speed train and moves, that is, the target device moves in synchronization with the vehicle such as the high-speed train, the time information of the target area where the target device arrives can be specified from the operating time information of the high-speed train.
The method for acquiring the running time information of the high-speed train includes various ways, for example, according to a preset running time table of the high-speed train, a time point or a time interval when the high-speed train runs to a target area can be determined; for another example, when a high-speed train runs to a target cell corresponding to a target area, a terminal device on the high-speed train accesses connection information generated by the target cell. And is not particularly limited herein. After the running time information of the high-speed train running to the target area is obtained, the running time information of the high-speed train can be used as the time information of the target equipment reaching the target area.
And step S102, determining a target weight vector according to the time information.
After the time information is obtained, the time when the high-speed train arrives at the target area can be determined. Therefore, according to the time when the high-speed train arrives at the target area, the cell corresponding to the target area can be set to be in the optimal signal coverage state in advance, and after the high-speed train arrives at the target area, the target equipment in the high-speed train can obtain the optimal signal coverage and signal connection state.
Specifically, the target weight vector is a parameter for controlling the base station to transmit a beam to a specific direction, and different weight vectors correspond to different coverage areas and directions; along with the movement of the high-speed train, the high-speed train continuously passes through and accesses different cells, the arrival of the train at a target area can be judged according to time information, and a determined target weight vector corresponding to the target area is further determined.
In one possible implementation, the time information and the target weight vector have a certain mapping relationship, for example, when the time information is from 8 point 0 to 8 point 2, the corresponding target weight vector is the weight vector a; according to the weight vector a, the signal coverage of the target area A can be realized.
And step S103, performing beam forming according to the target weight vector to perform signal coverage on the target area.
Fig. 3 is a schematic diagram of beam forming provided in an embodiment of the present application, and as shown in fig. 3, a 5G base station is provided with a large-scale antenna structure, and data streams are mapped onto different antenna sub-oscillators after being weighted by digital weights to form a beam conforming to an expected direction and width. Specific beamforming processes such as signal processing and digital-to-analog conversion are prior art in the art, and are not described herein again.
Here, it should be noted that in the present embodiment, a high-speed rail scene is taken as an example for description, and it is understood that the method provided in the present embodiment is also applicable to other scenes, for example, a highway signal coverage scene, that is, a target device is a terminal device installed on an automobile running at a high speed; or a river, a shoreline signal coverage scenario, i.e. the target device is a terminal device arranged on a vessel moving along the shoreline or the river. One example is not illustrated here.
In the embodiment, the time information of the target device reaching the target area is obtained, the target weight vector is determined according to the time information, and the beam forming is performed according to the target weight vector to cover the target area.
Fig. 4 is a flowchart of a beamforming control method according to another embodiment of the present application, and as shown in fig. 4, the beamforming control method according to this embodiment further refines steps S101 to S102 on the basis of the beamforming control method according to the embodiment shown in fig. 2, and adds a step of resident signal migration after S101, where a target area includes a target cell, and the beamforming control method according to this embodiment includes the following steps:
step S201, user connection information in the target cell is acquired.
Taking a high-speed rail scene as an example, because wireless signals of the private network and the public network of the high-speed rail are inevitably overlapped in a staggered manner, for a target cell, users who access the target cell through the terminal equipment include resident users who are in or near the cell for a long time, and also include high-speed rail users who take a high-speed rail train when the high-speed rail train passes through. The user connection information may represent specific information of the resident user and/or the high-speed rail user accessing the target cell, such as access quantity, access time, and the like.
Step S202, according to the time domain characteristics of the user connection information, the time information of the target device reaching the target cell is determined.
Fig. 5 is a schematic diagram of time domain characteristics of user connection information according to an embodiment of the present application, where as shown in fig. 5, the user connection information may be a mapping relationship between access number and access time, and the access number of the user changes with the change of the access time, and when a large pulse appears on a curve as shown in fig. 5, a large burst access number is shown, and the time domain characteristics correspond to a real situation that a large number of users in a high-speed train are connected to a target cell through a terminal device after the high-speed train drives into a target area.
For example, the user connection information may be historical user connection information of the target cell, such as the number of accesses and access time corresponding to the same train running according to a fixed train schedule when the target cell is driven into for several days.
Optionally, the time-domain feature includes a time-domain periodic pulse, as shown in fig. 6, step S202 includes two specific implementation steps S2011 and S2012:
step S2021, a time domain periodic pulse of the user connection information is acquired.
The target cell corresponding to the high-speed rail private network is often shared by normal users on non-high-speed rails and users on high-speed rails, and the number of the users in the cell shows periodic pulse distribution. Taking the time dimension of 1 hour as an example, it can be seen that the number of users in a cell is very high when a train passes through, and the pulses repeatedly appear according to a certain time period.
Step S2022, determining time information of the target device reaching the target cell according to the distribution of the time domain periodic pulse.
Fig. 7 is a schematic diagram of a time-domain periodic pulse provided in an embodiment of the present application, and as shown in fig. 7, the number of users accessing a target cell in a time domain shows the distribution of the periodic pulse, and according to the distribution of the time-domain periodic pulse, the time when a train reaches the target cell, that is, the time when a target device reaches the target cell, may be determined.
Step S203, acquiring a preset base station connection model; the base station connection model is used for representing a base station connection rule in the target area.
Illustratively, the base station connection model is used for characterizing the connection rules of the base stations in the target area, for example, a resident user has a long time to access the base stations in the target area every day because the resident user is in or around the target area for a long time; however, the high-speed rail user can access the base station in the target area through the terminal device only when the high-speed rail passes through the target area, and therefore, different types of users have different access characteristics, namely, the connection rule of the base station, when accessing the base station through the terminal device. According to the base station connection rule, different types of users can be distinguished.
Step S204, according to the base station connection model, the resident signal connected with the base station in the target area is transferred to the base station in the non-target area.
Specifically, the resident signal is a connection signal of a resident device connected to the base station in the target area.
Optionally, the time information includes a target time window, and the target time window is used to represent the time when the target device reaches the target area, as shown in fig. 8, step S204 includes two specific implementation steps of steps S2041 and S2042:
step S2041, determining a target time window according to the base station connection model, wherein the target time window is used for representing the time when the target equipment reaches the target area.
Since the time when the target device reaches the target area is estimated and counted from the historical data, there is a certain error. In order to ensure that good information coverage can be obtained quickly when the target device moves to the target area, an error allowable range is added to the time when the target device reaches the target area, and a target time window is formed.
Specifically, the base station connection model includes a rule description of the high-speed rail user when connecting with the base station through the terminal device, so that according to the base station connection model, the specific access time and the change condition of the access number of the high-speed rail user accessing the base station in the target area can be determined, and further, according to the change condition of the access time and the access number, a proper target time window is determined.
The process of determining the target time window is described below in one embodiment.
Fig. 9 is a schematic diagram of a target time window according to an embodiment of the present disclosure, as shown in fig. 9, A, B, C are three pulses formed by increasing the access number of the high-speed railway user, and the change trend of the access number of the high-speed railway user is obviously different from the change trend of the access number of the resident user in the target area. According to A, B, C three pulses, three time windows a, b and c are formed correspondingly. Meanwhile, according to the base station connection model, it can be known that the intervals between A, B, C and three pulses are all less than 5 minutes, and the intervals can be regarded as corresponding to high-speed rail users in the same train of high-speed rails, so that a large time window d, namely a target time window, is determined according to A, B, C and three pulses.
Step S2042, in the target time window, migrating the resident signal connected to the base station in the target area to the base station in the non-target area.
Illustratively, the number of users in the private network cell per second level is extracted, the specific time when the train reaches the target cell is obtained by utilizing the characteristic that the number of users presents periodic pulse distribution when the train arrives, and then a time error allowable value is added to the specific time to form a train arrival time window. And then, in the time window, scheduling operation is carried out on the current resident signal of the target cell according to the base station connection model.
The statistical period for extracting the number of users in the second level per day in the private network cell can be various, and within a certain range, the longer the statistical period is, the more accurate the statistical result is, but the higher the time cost of the extraction process is, the facility can be implemented according to specific needs, and the specific limitation is not performed here.
Step S205, signal strength information in the target time window is acquired.
Illustratively, the signal strength information preset in the target time window is information representing signal strength obtained by performing a test in the target time window after a target area is covered by a conventional adaptive beamforming method. The signal strength information may be obtained through pre-acquired historical signal strength information, or may be obtained through signal coverage by a conventional adaptive beamforming method and triggering signal strength acquisition within a target time window, where a method for acquiring the pre-acquired signal strength information is not limited herein.
Step S206, determining a target weight vector according to the signal intensity information.
Optionally, the signal strength information is used to characterize the signal strength of each weight vector, where each weight vector corresponds to multiple signal strength values; as shown in fig. 10, step S206 includes two specific implementation steps S2061 and S2062:
step S2061, obtaining signal strength values corresponding to the weight vectors.
In the general adaptive beam forming mode, in each scheduling period, the Signal strength of the terminal devices of n high-speed rail users on each high-speed rail train under a beam forming weight vector, that is, the Reference Signal Receiving Power (RSRP), is obtained, and the Signal strength values corresponding to the weight vectors, that is, the RSRP values of the terminal devices of the n high-speed rail users corresponding to m different beam forming weight vectors W in a target time window, are obtained.
Step S2062, determining the target weight vector according to the mean value of the signal strength values corresponding to the weight vectors and the ratio of the good signal strength values corresponding to the weight vectors.
Specifically, the good duty ratio value is used to represent a duty ratio greater than a preset signal strength threshold value in a plurality of signal strength values corresponding to the weight vector.
Illustratively, the weight vector includes a plurality of sub-weight vectors, and each sub-weight vector corresponds to a signal strength value. Presetting the signal intensity threshold value as the average value of the signal intensity of the terminal equipment of n high-speed rail users
The mean value->
Different weight vectors correspond to different signal intensity thresholds for calculation according to historical data and are preset in a storage medium. Calculating the signal intensity mean value between each sub-weight vector of each weight vector and the terminal equipment of n high-speed rail users
Then will >>
Is compared with a predetermined reasonable signal coverage strength R if->
This indicates good signal strength, and conversely this indicates poor signal strength. Calculating a mean value of signal strengths corresponding to each sub-weight vector in each weight vector>
For a good occupation ratio value, a sequence ordered according to the magnitude of the good occupation ratio value can be obtained, and then, the weight vector corresponding to the maximum occupation ratio value, even if the connection signal of the base station and the target device is good, and the weight vector with stable connection is determined as the target weight vector.
Fig. 11 is a schematic diagram of determining a target weight vector according to an embodiment of the present application, as shown in fig. 11, in a possible implementation manner, when determining the target weight vector according to a signal strength value corresponding to each weight vector, if there is a unique weight vector in each weight vector, the good fraction value of the corresponding signal strength value is the largest, and the mean value of the corresponding signal strength values is greater than a preset signal coverage threshold, the unique weight vector is determined as the target weight vector. Fig. 12 is another schematic diagram for determining a target weight vector according to an embodiment of the present application, as shown in fig. 12, in another possible implementation manner, if at least two weight vectors exist in each weight vector, and it is satisfied that a good ratio of corresponding signal intensity values is the largest, and a mean value of corresponding signal intensity values is greater than a preset signal coverage threshold, a mean value of signal intensity values in the at least two weight vectors is larger, and is determined as the target weight vector.
In a possible implementation manner, if the mean value of the signal strength values corresponding to the weight vectors is smaller than the preset signal coverage threshold, it indicates that the signal coverage effect of the currently adopted beamforming method is very poor, or even the effect is good without the traditional adaptive beamforming method, and therefore, the target cell may have a problem, that is, the target cell is a problem cell. Optionally, alarm information of the problem cell may be output for giving a prompt to an external system or a user.
Step S207, performing beamforming according to the target weight vector to perform signal coverage on the target region.
Fig. 13 is a comparison graph of the good duty ratio of the signal strength generated by the beam forming method provided in the embodiment of the present application and the signal strength generated by the conventional beam forming method, as shown in fig. 13, when the beam forming method provided in the embodiment of the present application is applied, the good duty ratio of the signal strength values is generally stable, the field strength at the beginning of each time window generally reaches a good level, and the good duty ratio of the signal strength values is significantly improved compared with the good field strength duty ratio of the general adaptive algorithm.
Therefore, by adopting the beam forming control method provided by the embodiment of the application, the signal can rapidly reach a good level after a high-speed rail user enters a high-speed rail cell, the signal strength is generally improved, and the user experience is improved.
In this embodiment, the implementation manner of step S207 is the same as the implementation manner of step S103 in the embodiment shown in fig. 2 of this application, and is not described in detail here.
Fig. 14 is a flowchart of a beamforming control method provided in another embodiment of the present application, and as shown in fig. 14, on the basis of the beamforming control method provided in the embodiment shown in fig. 4, a step of checking and correcting is added after step S207 in the beamforming control method provided in this embodiment, then the beamforming control method provided in this embodiment includes the following steps:
step S301, user connection information in the target cell is obtained.
Step S302, according to the time domain characteristics of the user connection information, determining the time information of the target device reaching the target cell.
Step S303, acquiring a preset base station connection model; the base station connection model is used for representing a base station connection rule in the target area.
Step S304, according to the base station connection model, migrating the resident signal connected with the base station in the target area to the base station in the non-target area, wherein the resident signal is a connection signal of the resident device connected with the base station in the target area.
In step S305, signal strength information in the target time window is obtained.
Step S306, determining a target weight vector according to the signal strength information.
And step S307, performing beam forming according to the target weight vector to perform signal coverage on the target area.
And step S308, acquiring signals of the target area according to preset acquisition configuration information to obtain a verification signal.
In a possible situation, when the mean value of the signal strength values corresponding to each weight vector is smaller than the preset signal coverage threshold, it indicates that the signal coverage effect of the currently adopted beamforming method is very poor, or even the effect is good without the traditional adaptive beamforming method, and therefore, the target cell may have a problem, that is, the target cell is a problem cell.
For example, the preset acquisition configuration information may include configuration parameters for performing a conventional adaptive beamforming method, and according to the preset acquisition configuration information, the conventional adaptive beamforming method is performed to cover the target area, and a signal of the target area is acquired by a terminal device or a test device of the target area and is used as a verification signal.
Step S309, calibrating the target weight vector according to the relationship between the signal strength of the target weight vector and the signal strength of the check signal.
Illustratively, the signal strength average value of the ith scheduling period is calculated by continuously sampling the signal strength values corresponding to the target weight vectors
And the field intensity mean value corresponding to the optimal weight vector under the traditional adaptive beam forming model
Performing a mean square deviation calculation, based on the mean square deviation>
If the mean square error σ is larger than the maximum allowable error σ max When the optimal weight is judged to have deviation, the observation and correction are needed, wherein the maximum allowable error sigma max The preset value can be determined according to the requirement. />
Then starting periodic sampling check, and calibrating the target weight vector, wherein the specific process comprises the following steps: 1 time of the universal adaptive beamforming sampling is recovered every 3 time windows, and 60 time windows are cumulatively sampled. In order to avoid the deviation caused by accidental reasons such as weather, the sampling delay time of the 60 time windows is set as the check waiting period, and it is understood that the number of the accumulated sampling time windows can be adjusted as required. During the waiting period, if the effect deviation returns to normal, that is to say
Stopping the sampling check mode, and continuing to use the original target weight vector; if the deviation is not recovered, judging that the deviation is not accidental and needs to be corrected, calculating a new target weight vector according to time window data under 20 traditional self-adaptive beam forming modes so as to ensure that a high-speed rail user can always keep the optimal experience.
Due to the influence of the change of physical parameters of a base station or the change of a wireless environment, the target weight vector can be changed for a short time or a long time, and the signal coverage effect is improved by setting an error checking and correcting mechanism for ensuring the continuous and optimal signal quality of the high-speed rail user.
In this embodiment, the implementation manners of step S301 to step S307 are the same as the implementation manners of step S201 to step S207 in the embodiment shown in fig. 4 of this application, and are not described in detail herein.
Fig. 15 is a schematic structural diagram of a beamforming control device according to an embodiment of the present application, and as shown in fig. 15, the beamforming control device 4 according to the embodiment includes:
an obtaining module 41, configured to obtain time information of the target device reaching the target area.
And a determining module 42, configured to determine the target weight vector according to the time information.
And a forming module 43, configured to perform beamforming according to the target weight vector, so as to perform signal coverage on the target area.
In one possible implementation, the target area includes a target cell; the obtaining module 41 is specifically configured to: acquiring user connection information in a target cell; and determining the time information of the target equipment reaching the target cell according to the time domain characteristics of the user connection information.
In a possible implementation manner, the time domain characteristic includes a time domain periodic pulse, and when determining, according to the time domain characteristic of the user connection information, time information of the target device reaching the target cell, the obtaining module 41 is specifically configured to: acquiring time domain periodic pulses of user connection information; and determining the time information of the target equipment reaching the target cell according to the distribution of the time domain periodic pulse.
In a possible implementation manner, the beamforming control apparatus further includes: the migration module 44 is configured to obtain a preset base station connection model after obtaining time information that the target device reaches the target area; the base station connection model is used for representing a base station connection rule in a target area; and migrating the resident signal connected with the base station in the target area to the base station in the non-target area according to the base station connection model, wherein the resident signal is a connection signal of resident equipment connected with the base station in the target area.
In a possible implementation manner, when migrating the resident signal connected to the base station in the target area to the base station in the non-target area according to the base station connection model, the migration module 44 is specifically configured to: determining a target time window according to the base station connection model, wherein the target time window is used for representing the time of target equipment reaching a target area; and migrating the resident signal connected with the base station in the target area to the base station in the non-target area in the target time window.
In a possible implementation manner, the time information includes a target time window, the target time window is used to characterize the time when the target device reaches the target area, and the determining module 42 is specifically configured to: acquiring signal intensity information in a target time window; and determining a target weight vector according to the signal strength information.
In one possible implementation, the signal strength information is used to characterize the signal strength of each weight vector; wherein each weight vector corresponds to a plurality of signal strength values; the determining module 42, when determining the target weight vector according to the signal strength information, is specifically configured to: obtaining signal strength values corresponding to the weight vectors respectively; and determining a target weight vector according to the mean value of the signal strength values corresponding to the weight vectors and the good ratio of the signal strength values corresponding to the weight vectors, wherein the good ratio is used for representing the ratio of a plurality of signal strength values corresponding to the weight vectors, which is greater than a preset signal strength threshold value.
In a possible implementation manner, the determining module 42 is specifically configured to, when determining the target weight vector according to the mean value of the signal strength values corresponding to the weight vectors and the good ratio of the signal strength values corresponding to the weight vectors: if the unique weight vector exists in each weight vector, the condition that the good occupation ratio of the corresponding signal intensity value is the largest is met, and the mean value of the corresponding signal intensity value is larger than a preset signal coverage threshold value, determining the unique weight vector as a target weight vector; if at least two weight vectors exist in each weight vector, the condition that the good occupation ratio of the corresponding signal intensity value is the largest is met, and the mean value of the corresponding signal intensity value is larger than a preset signal coverage threshold value, the mean value of the signal intensity values in the at least two weight vectors is larger, and the weight vector is determined as a target weight vector.
In a possible implementation manner, the beamforming control apparatus further includes: the calibration module 45 is configured to, after determining a target weight vector according to the time information, perform signal acquisition on the target area according to preset acquisition configuration information to obtain a calibration signal; and calibrating the target weight vector according to the relation between the signal strength of the target weight vector and the signal strength of the check signal.
The obtaining module 41, the transferring module 44, the determining module 42, the shaping module 43, and the calibrating module 45 are connected in sequence. The beamforming control apparatus 4 provided in this embodiment may execute the technical solutions of the method embodiments shown in fig. 2 to fig. 14, and the implementation principle and the technical effect are similar, and are not described herein again.
Fig. 16 is a schematic structural diagram of an electronic device according to an embodiment of the present application, and as shown in fig. 16, the electronic device according to the embodiment may be applied to a base station, and the electronic device includes: a memory 51, a processor 52 and a computer program.
Wherein the computer program is stored in the memory 51 and configured to be executed by the processor 52 to implement the beamforming control method provided by any of the embodiments corresponding to fig. 2-14 of the present application.
The memory 51 and the processor 52 are connected by a bus 53.
The relevant description may be understood with reference to the relevant description and effect corresponding to the steps in the embodiments corresponding to fig. 2 to fig. 14, and redundant description is not repeated here.
An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the beamforming control method provided in any of the embodiments corresponding to fig. 2 to fig. 14 of the present application.
The computer readable storage medium may be, among others, ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of modules is merely a division of logical functions, and an actual implementation may have another division, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (10)
1. A method for beamforming control, the method comprising:
acquiring time information of target equipment reaching a target area;
determining a target weight vector according to the time information;
according to the target weight vector, carrying out beam forming to cover the target area with signals;
the time information includes a target time window, the target time window is used for representing the time when the target device reaches the target area, and the determining of the target weight vector according to the time information includes: acquiring signal intensity information in the target time window; determining a target weight vector according to the signal intensity information;
the signal strength information is used for representing the signal strength of each weight vector; wherein each weight vector corresponds to a plurality of signal strength values; determining a target weight vector according to the signal strength information, comprising: acquiring signal strength values respectively corresponding to the weight vectors; and determining a target weight vector according to the mean value of the signal strength values corresponding to the weight vectors and the good proportion value of the signal strength values corresponding to the weight vectors, wherein the good proportion value is used for representing the proportion of a plurality of signal strength values corresponding to the weight vectors, which is greater than a preset signal strength threshold value.
2. The method of claim 1, wherein the target area comprises a target cell; acquiring time information of a target device reaching a target area, comprising:
acquiring user connection information in a target cell;
and determining the time information of the target equipment reaching the target cell according to the time domain characteristics of the user connection information.
3. The method of claim 2, wherein the time domain characteristics comprise time domain periodic pulses, and wherein determining the time information of the target device reaching the target cell according to the time domain characteristics of the user connection information comprises:
acquiring time domain periodic pulses of user connection information;
and determining the time information of the target equipment reaching the target cell according to the distribution of the time domain periodic pulse.
4. The method of claim 1, after obtaining the time information of the target device reaching the target area, further comprising:
acquiring a preset base station connection model; the base station connection model is used for representing a base station connection rule in the target area;
and migrating the resident signal connected with the base station in the target area to the base station in the non-target area according to the base station connection model, wherein the resident signal is a connection signal of resident equipment connected with the base station in the target area.
5. The method of claim 4, wherein migrating the resident signals connected to the base station in the target area to the base station in the non-target area according to the base station connection model comprises:
determining a target time window according to the base station connection model, wherein the target time window is used for representing the time of the target equipment reaching a target area;
and migrating the resident signal connected with the base station in the target area to the base station in the non-target area in the target time window.
6. The method of claim 1, wherein determining the target weight vector according to the mean of the signal strength values corresponding to the weight vectors and the good fraction of the signal strength values corresponding to the weight vectors comprises:
if a unique weight vector exists in each weight vector, the condition that the good occupation ratio of the corresponding signal intensity value is the maximum and the mean value of the corresponding signal intensity value is greater than a preset signal coverage threshold value is met, determining the unique weight vector as a target weight vector;
if at least two weight vectors exist in each weight vector, the condition that the good occupation ratio of the corresponding signal intensity value is the largest is met, and the mean value of the corresponding signal intensity value is larger than a preset signal coverage threshold value, the mean value of the signal intensity values in the at least two weight vectors is larger, and the weight vector is determined as a target weight vector.
7. The method according to any of claims 1-6, further comprising, after determining a target weight vector from the temporal information:
acquiring signals of the target area according to preset acquisition configuration information to obtain a check signal;
and calibrating the target weight vector according to the relation between the signal intensity of the target weight vector and the signal intensity of the check signal.
8. A beamforming control apparatus, comprising:
the acquisition module is used for acquiring the time information of the target equipment reaching the target area;
the determining module is used for determining a target weight vector according to the time information;
the shaping module is used for carrying out beam shaping according to the target weight vector so as to carry out signal coverage on the target area;
the time information comprises a target time window, the target time window is used for representing the time when the target equipment reaches a target area, and the determining module is specifically used for acquiring signal strength information in the target time window; determining a target weight vector according to the signal intensity information;
the signal strength information is used for representing the signal strength of each weight vector; wherein each weight vector corresponds to a plurality of signal strength values; the determining module is specifically further configured to obtain signal strength values corresponding to the weight vectors respectively; and determining a target weight vector according to the mean value of the signal strength values corresponding to the weight vectors and the good proportion value of the signal strength values corresponding to the weight vectors, wherein the good proportion value is used for representing the proportion of a plurality of signal strength values corresponding to the weight vectors, which is greater than a preset signal strength threshold value.
9. An electronic device, comprising: a memory, a processor, and a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the beamforming control method according to any of claims 1 to 7.
10. A computer-readable storage medium having computer-executable instructions stored thereon, which when executed by a processor, are configured to implement the beamforming control method according to any of claims 1 to 7.
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